First Plant Cell Atlas symposium report

Abstract The Plant Cell Atlas (PCA) community hosted a virtual symposium on December 9 and 10, 2021 on single cell and spatial omics technologies. The conference gathered almost 500 academic, industry, and government leaders to identify the needs and directions of the PCA community and to explore how establishing a data synthesis center would address these needs and accelerate progress. This report details the presentations and discussions focused on the possibility of a data synthesis center for a PCA and the expected impacts of such a center on advancing science and technology globally. Community discussions focused on topics such as data analysis tools and annotation standards; computational expertise and cyber‐infrastructure; modes of community organization and engagement; methods for ensuring a broad reach in the PCA community; recruitment, training, and nurturing of new talent; and the overall impact of the PCA initiative. These targeted discussions facilitated dialogue among the participants to gauge whether PCA might be a vehicle for formulating a data synthesis center. The conversations also explored how online tools can be leveraged to help broaden the reach of the PCA (i.e., online contests, virtual networking, and social media stakeholder engagement) and decrease costs of conducting research (e.g., virtual REU opportunities). Major recommendations for the future of the PCA included establishing standards, creating dashboards for easy and intuitive access to data, and engaging with a broad community of stakeholders. The discussions also identified the following as being essential to the PCA's success: identifying homologous cell‐type markers and their biocuration, publishing datasets and computational pipelines, utilizing online tools for communication (such as Slack), and user‐friendly data visualization and data sharing. In conclusion, the development of a data synthesis center will help the PCA community achieve these goals by providing a centralized repository for existing and new data, a platform for sharing tools, and new analytical approaches through collaborative, multidisciplinary efforts. A data synthesis center will help the PCA reach milestones, such as community‐supported data evaluation metrics, accelerating plant research necessary for human and environmental health.

Single cell transcriptomics of developing and mature leaf types could recover 90,000 cells. Known markers could be applied to identify many of these cell types. In a glandlike cell cluster, some subclusters are specific to the pitcher leaves and express known digestive enzymes; thus, these are likely the cell types responsible for digestion. These data also led to new marker genes associated with digestive cells. Many pitcher-specific cell types were related to epidermal cell types, some of which appear to represent the imbricate hairs. During the development of this cell type, early cell clusters emerged in the pitcher leaves, which are involved in stress response and possibly growth inhibition. Later developmental cell clusters were related to modified cell wall properties. Thus, the cell types around the entrance and inside the pitcher should be restricted in growth, and stress-response-related genes might regulate this process, providing insights into the development of the pitcher shape.
Key takeaways: Single-cell sequencing and advanced imaging techniques can enhance our understanding of non-model organisms and the evolution of novel cell types in carnivorous plants.

A high-resolution single-cell atlas of shoot meristems at cross-species and multimodal levels
Speaker: Xiaosa Xu, Cold Spring Harbor Laboratory, USA The plant shoot meristem determines the architecture of a plant; thus, understanding this system is important to inform future work seeking to design crops with improved performance. Dr. Xu's work aims to clarify how the shoot meristem is regulated in maize and Arabidopsis throughout its lifecycle. Localized expression of master regulators drives plant development. Dr. Xu first performed single-cell RNA sequencing (RNA-seq) on developing maize ear and identified and validated 12 cell groups marking distinct cell-types or developmental domains. However, the rare stem cells were not recovered.
A similar challenge was also reported in an Arabidopsis shoot meristem single-cell study. Thus, Dr. Xu finely dissected the developing maize ear tip to enrich stem cells. Dr. Xu also profiled Arabidopsis apetala1; cauliflower double mutants, which proliferate to produce many shoot meristems. Dr. Xu successfully recovered stem cells for both species and identified and validated conserved stem cell markers. To further understand stem cell proliferation in maize, Dr. Xu then profiled the ear tip of fea3; Zmcle7 double mutants, which were strongly fasciated, and identified a family of metabolic genes that play a role in shoot stem cell development.
Dr. Xu also examined plant gene regulation at single-cell level. Accessible chromatin regions are often associated with regulatory elements that control gene expression. Single-cell ATAC sequencing (ATAC-seq) can probe this level of regulation. By integrating maize single-cell RNA-seq and single-cell ATAC-seq datasets of developing maize ear and tassel, Dr. Xu identified cell-type-specific accessible chromatin regions associated with gene expression in maize inflorescences. Future work using CRISPR to generate cis-regulatory alleles will aid in elucidating the function of these regions and ultimately improving crop performance.
Key takeaways: Single-cell RNA sequencing is highly effective for capturing plant stem cell niches. Integrating single-cell RNA sequencing and ATAC sequencing provides essential information about accessible chromatin regions associated with gene expression in plants.

Unveiling spatial host-microbiome interactions by applying spatial metatranscriptomics
Speaker: Stefania Giacomello, SciLifeLab -KTH, Sweden Dr. Giacomello's research focuses on how cell gene expression influences the spatial organization of cells and how the location of cells influences cell communication and interactions. Originally developed for animal tissues, spatial transcriptomics has been applied to plants to study high-resolution, spatially resolved profiles. 10X Genomics has commercialized this technology with a higher spatial resolution compared with the original development.
Recent work has focused on advancing this technology in order to study the spatial organization of microbes on Arabidopsis leaves. The goals were to clarify the host response to microbe clusters and to understand microbe-microbe abundances at the spatial level. To this end, Dr. Giacomello's group developed spatial metatranscriptomics (SmT). This technology provides three readouts, one each for the host, microbes, and fungi. Experiments using infiltrating mCherry-tagged Pseudomonas demonstrated that the SmT approach can capture spatial information of the microbe. To validate this approach, the group compared their results with those obtained via the gold standard of the field, amplicon sequencing. This comparison showed that the SmT array can capture more microbial information than amplicon sequencing. Quantified bacterial and fungal profiles showed consistency across leaves of the same plants.
Next, Dr. Giacomello's group investigated the spatial organization of microbes on outdoor leaves. Hotspot analysis revealed significant colocalization of microbes on tissue sections. The bacteria showed substantially more hotspots than fungi, but there were instances of colocalization between the bacteria and fungi. Overall, there was a consistent number of microbial interactions across leaves of the same plant. By associating microbial interactions with hotspot analysis, the group concluded that spatial locations drive intra-and inter-kingdom interactions. Finally, photosynthesis-related genes and immune-related genes exhibited high expression at microbial hotspot locations.
At the base of the floral organs, the floral nectaries consist of specialized secretory tissue. To study the nectary population, Dr. Nikolov's lab generated single-cell transcriptome profiles of the flowers of crabs claw mutants that lack nectaries and then pinpointed a specific cell cluster that was absent in these mutants. This cell population appears to be very metabolically active based on gene co-expression network analysis. This effort revealed that SWEET9 and TPS24 expression depends on CRABS CLAW (CRC). Similarly, CWINV4 expression depends on CRC in the nectary, however not in the companion cells. This finding suggests that factors other than CRC control expression in the companion cells. Indeed, the networks are non-overlapping between the companion cells and the nectary. Thus, single-cell perturbation approaches are powerful for studying gene regulation in different cells.
Key takeaway: A comprehensive catalog of floral cell types has led to crucial insights into the transcriptomes of rare cell types, diversity in known cell types, and new cell types. Floral gene co-expression network analyses of secretory cells can reveal master regulators and downstream targets.

Oral Session 3
1. Regulatory dynamics of germinating seeds from bulk tissue to single-cell resolution Speaker: Mathew G. Lewsey, La Trobe University, Australia The Lewsey lab seeks to clarify how seed germination occurs and is regulated. It is critical that this process be correctly controlled and in tune with environmental conditions because if the seed germinates at the wrong time, the plant will not grow.
How much does gene expression change over time during germination and how is this process controlled? To answer this question, Dr. Lewsey's group performed bulk gene expression analysis and identified 24,283 differentially regulated genes during the germination process in Arabidopsis seeds. These genes fell into interesting clusters of regulation: a transient upregulated cluster during the transition from stratification in darkness to light, a late upregulated cluster during the metabolic transition of light, and a downregulated cluster during early germination. In concert with these processes, a broad loss of methylation occurs in the genome, and large dynamic changes correlate with the transitions in small RNAs. Although these data are useful for building transcriptional models, there are limitations to using a bulk approach. The Arabidopsis seed has multiple tissues and organs, which are all composed of different cell types. Moreover, these cell types perform different functions at different times. Thus, Dr. Lewsey's work has shifted toward single-cell approaches.
Recent work has focused on measuring gene expression in single Arabidopsis cells at three time points of germination (early, mid, and late). A comparison of bulk RNA sequencing between protoplast and the non-protoplast samples clarified the effect of protoplast isolation on Arabidopsis seeds. This effort identified several genes that were differentially regulated due to protoplast isolation but were not dependent on the germination time point. Next, a single-cell RNA sequencing experiment investigated different time points in order to identify clusters of similar cells and annotate cell identities. This step is challenging because there are no defined maps to serve as the ground truth for single-cell RNA sequencing in seeds. Instead, Dr. Lewsey's group combed through the literature to determine marker transcripts that identify cell types and annotated clusters on the resulting t-distributed stochastic neighbor embedding plots. The clusters were specific to provascularture, cotyledon, hypocotyl, and radicle cells. The group then used these clusters to define new marker genes and validate the cluster annotations in plants. These experiments also led to the discovery of cluster transitions over time, likely representing transitions to different transcriptional cell states. For such a transition to occur, one would expect high levels of transcriptional activity to allow the cells to reprogram. Indeed, using RNA velocity as a metric to measure transcription, the group detected a high level of active transcription across the clusters, associated with cell state changes. Future work will focus on understanding how this movement along a transcriptional trajectory is controlled.
Key takeaways: Substantial remodeling of gene expression occurs during germination. As seeds are complex structures composed of many cell types, single-cell methods allow researchers to better characterize which cell types are active at different locations and time points during germination.

Single-nucleus RNA and ATAC sequencing reveals the impact of chromatin accessibility on gene expression in Arabidopsis roots at the single-cell level
Speaker: Marc Libault, University of Nebraska-Lincoln, USA Dr. Libault's lab uses isolated plant nuclei to characterize the transcriptome and patterns of chromatin accessibility in Arabidopsis cells. Nuclei present many advantages over protoplasts for characterizing plants at the single-cell level: they are easier to generate than protoplasts, they strongly minimize size discrimination in microfluidic platforms, and their RNAs better represent newly synthesized transcripts to capture initial cellular responses. Single-nucleus RNA sequencing technology enables researchers to characterize plant cell transcriptomes for identifying differentially expressed genes. With this approach, Dr. Libault's group revealed the transcriptome of new Arabidopsis root cell types and then performed functional annotation using root cell-type marker genes.
Dr. Libault's group also aims to elucidate how plant genomes are read, regulated, organized, and expressed, especially in response to environmental stresses, using single-nucleus omics technologies. Ultimately, this knowledge could be translated to improve crop productivity and quality. With this approach, Dr. Libault has interrogated the sequence of transcriptional events controlling plant development, plant cell differentiation, and plant cell responses to stress, allowing the development of accurate gene networks. For example, single-nucleus ATAC sequencing technology can reveal discrete changes in chromatin accessibility. Comparative analyses suggest a correlation between gene expression and chromatin accessibility. Therefore, transcriptomic and epigenomic changes occurring at the single-cell level make it possible to infer causal relationships with high accuracy.
The lab is expanding this work to include other species beyond Arabidopsis such as soybean, Medicago, and sorghum. Thus, single-nucleus omics technologies are applicable to different plant species and tissues for enhancing the functional characterization of plant genes.
Key takeaways: Isolated plant nuclei can provide biologically meaningful transcriptomic information at the single-cell level. Chromatin accessibility at the location of the transcription start site of selected genes can act as a molecular marker of cell-type identity.

Mapping cellular divergence in crop plants via comparative single-cell and nuclear analysis
Speaker: Bruno Guillotin, New York University, USA Within Dr. Birnbaum's lab, Dr. Guillotin has focused on comparing cell types across species to obtain access to a new evolutionary concept of cellular divergence. This work started with a complete study of cell-type evolution across species. Zea mays is a wellstudied plant with numerous marker genes and genetic tools available; thus, this work aimed to use this knowledge to study other interesting but less-studied plants, including Sorghum bicolor and Setaria viridis. Is it possible to map cell types from one species to another using the rich knowledge of one plant species (in this case, Zea mays)? Can we ultimately compare cell types across species to determine whether certain cell types are evolving faster than others? To begin addressing these questions, Dr. Guillotin and his colleagues utilized both single-cell and single-nucleus RNAseq approaches. Combining these approaches in all three plant species enabled the team to identify every cell type in the species. The group is now validating these cell types with a newly developed whole-mount in situ hybridization approach.
In addition, by comparing the cellular transcriptomes across species, Dr. Guillotin has analyzed differential evolution. In the three species analyzed, the epidermis layers showed stable transcriptomes. By contrast, the cortical layers showed lower conservation scores, indicating divergence across species. Interestingly, the columella was the most divergent of all the cell types and appears to be a quickly evolving cell type in Zea mays compared with Setaria viridis. Some of the most divergent genes were expressed in maize columella, with many of these genes involved in mucilage production. These findings are consistent with differences in these species in the routing of mucilage production.

Key takeaways:
Performing direct cell-type identification across species enabled the detection of a rapidly evolving cell type and associated molecular processes. This approach is valuable for mapping traits in crop species. The Gene Expression Team of EMBL-EBI, led by Irene Papatheodorou, is developing an array of functional genomics resources. The EBI collects data from the community and then validates and stores the data in an archive. The EBI also integrates and visualizes data for the research community. Annotare is a data submission tool that captures plant single-cell sequencing data, including technical, protocol, and annotation information. Submission templates are tailored to different experiments and technologies.
Once data are submitted, the data are available for analysis and visualization in the Single-Cell Expression Atlas. The goal of this freely available resource is to provide information on where and under what conditions different genes are expressed at a single-cell level. The atlas includes analysis results for almost 6 million cells across 229 single-cell studies in 18 species, including human, mouse, and fly, and 19 plant datasets across 4 species. With this resource, users can explore questions such as where a particular gene is expressed at the single-cell level and whether a gene defines a specific cell population. For each dataset, the atlas also includes the underlying metadata, raw result files, associated publications, and analysis methods and workflows. The Single-Cell Expression Atlas also works in partnership with other atlases, such as the Human Cell Atlas.
Key takeaway: Resources such as the Single-Cell Expression Atlas are only possible because of species-specific atlas efforts such as the PCA that bring communities together and define minimum standards to allow the reanalysis of data generated by experts.

Integration of cell-type-specific omics analysis towards a spatiotemporal understanding of molecular responses to abiotic stresses in poplar
Speaker: Vimal Kumar Balasubramanian, Pacific Northwest National Laboratory, USA Abiotic stresses, such as heat, drought, and salinity, are major challenges in future food and bioenergy crop production. Within Dr. Ahkami's research group, Dr.
Balasubramanian studies different combinations of abiotic stresses in poplar leaves and roots. Each cell type in plant tissue is defined by specific molecular profiles that determine its response to stress. Using integrated spatially resolved single-cell omics, the goals of Dr. Balasubramanian's work are to unravel new elements of plant responses to single and multiple stresses and to map molecular machineries to cellular domains. From investigations of poplar leaf and root cell types, leaf palisade and vascular cells have emerged as exhibiting unique cell-type-specific gene expression patterns under stress. In addition, the combined effect of salinity and heat revealed possible roles of the enzymes zeaxanthin epoxidase and galactinol synthase in specific poplar cell types. Although these enzymes have been linked to heat stress tolerance in previous whole tissue-based studies, using a spatial approach made it possible to identify distinct upregulations in particular cell types.
Further work applied the nanoPOTS (nanodroplet processing in one pot for trace samples) platform for cell-type-specific proteomics analysis of a small number of plant cells. This approach revealed leaf and root cell-type-unique and -shared proteins. Using the optimized nanoPOTS pipeline, Dr. Balasubramanian and his colleagues identified unique candidate cell-type-specific stress-responsive proteins. At the cellular level, a discordance emerged between the transcript and protein abundance data. This finding could suggest a critical layer of regulatory processes at the post-translational level, celltype-specific variations in splicing patterns, or factors such as mRNA export or protein stability. Finally, mass spectrometry imaging can enable spatiotemporal metabolite visualization.

Key takeaway:
The combination of cell-type transcriptome, proteomic, and metabolic technologies can reveal meaningful information to elucidate cell-type-specific stress responses in plants.

Identification of cell-type specific gene regulatory networks in plants using MINI-EX, a Motif-Informed Network Inference method based on single-cell EXpression data
Speaker: Camilla Ferrari, VIB-Ghent University, Belgium Single-cell transcriptomics is a growing goldmine in plants, allowing gene expression levels to be measured in different cell-types. However, single-cell transcriptomics is not sufficient for studying cell-type-specific organization. Dr. Ferrari couples single-cell transcriptomics with gene regulatory network inference through a newly developed method called MINI-EX. This method uses gene expression and transcription factor binding information to infer cell-type-specific gene regulatory networks. MINI-EX is currently available for three plant species: Zea mays, Oryza sativa, and Arabidopsis thaliana. MINI-EX is executed in three steps: (1) expression-based network inference, (2) transcription factor binding site enrichment, and (3) target gene and transcription factor expression filtering. Compared with existing gold-standard methods (i.e., GRNBoost2 and SCENIC), MINI-EX achieved higher performance metrics.
By applying MINI-EX on an Arabidopsis root single-cell RNA sequencing dataset composed of ~15,000 cells, ~19,000 expressed genes, 41 cell clusters, and 14 cell types Dr. Ferrari identified ~4,000 regulons for ~700 transcription factors. With such a large number of regulons, the next goal was to determine how to correctly prioritize transcription factors relevant for the regulation of a specific organ or condition. For this aim, Dr. Ferrari used a weighted metric that considers the specificity of expression, the importance of the transcription factor for the network of the associated cell-type, and the functional relevance of the target genes. With this metric, MINI-EX was able to identify known root regulators, providing a proof of concept. In addition, MINI-EX identified novel transcription factors linked to root-regulated phenotypes that are likely to be primary regulators.
Key takeaway: Specifically designed for plants, MINI-EX integrates single-cell gene expression and transcription factor motif information to infer cell-type-specific gene regulatory networks and efficiently prioritizes promising candidates for functional characterization studies.

Integrating spatial transcriptomics and 3D imaging in plants
Speaker: Kevin Cox, Jr., Donald Danforth Plant Science Center, USA For plants to regulate development and responses to abiotic or biotic stresses, they must communicate. Cell-to-cell communication begins with environmental stimuli, which then triggers inter-and intra-cellular signaling. One key communication means is transcriptional regulation or gene expression. RNA-sequencing is useful for transcriptional analysis in plants, but is limited when performed on bulk tissue, as it fails to resolve spatial and temporal heterogeneity. Spatial transcriptomics is a relatively new technology that allows the preparation of RNA-sequencing libraries from tissue sections, while retaining spatial information.
Within Dr. Meyers' group, Dr. Cox has worked toward increasing the resolution of spatial transcriptomics to a single-cell level by applying maskless array synthesis via photolithography. To reduce the sequence error rate of the microarrays, Dr. Cox shortened the length synthesized on the array. In preliminary experiments, the new high-resolution microarrays for spatial transcriptomics successfully captured mRNA in Wolffia microscopica. The next step will be to further optimize the method for RNAsequencing. In addition, Dr. Cox demonstrated that X-ray microscopy can be used to generate detailed 3D volume image data in Wolffia microscopica. Thus, the combination of spatial transcriptomics and 3D imaging provides a powerful new approach for illustrating gene expression localization. Ultimately, this method could elucidate plantmicrobe interactions at a single-cell resolution.

Key takeaway:
The combination of spatial transcriptomics and 3D imaging technologies can better define transcript abundance patterns across complex plant tissues and organs in a multi-dimensional context.

Mapping plant-mycorrhizal interactions with spatial transcriptomics and single-nuclei sequencing
Speaker: Margot Bezrutczyk, Lawrence Berkeley National Lab, USA Symbiosis between plants and arbuscular mycorrhizal fungi (AMF) is critical for agriculture. Plants provide AMF with carbon, and in exchange, AMF provide the plant with phosphorous, nitrogen, and water, partly by acting as a physical extension of the plant's root system. The expected density and yield of modern crops are impossible to achieve without a supplemental phosphate chemical fertilizer. It is expected that we will reach peak phosphorus mining within this decade. Thus, a better understanding of biotic sources of phosphates is critical for the future of agriculture.
During mutualistic symbiosis, AMF grow extensively within the root, both in between and inside the cells. The hypha of the fungus differentiates to form a highly branched structure called an arbuscule. The development of this structure requires high levels of transcriptional changes. Dr. Bezrutczyk and her colleagues study these changes using single-nuclei sequencing and spatial transcriptomics. With Medicago truncatula as a plant model and Rhizophagus irregularis as the AMF, single-nucleus sequencing has revealed a variety of cell types, cell states, and new marker genes.
Medicago gint1 mutants, which fail to form arbuscules, present an ideal model for studying different stages of symbiosis formation. By comparing the transcriptomes of wild-type and gint1 Medicago, Dr. Bezrutczyk is working to delineate the stages of arbuscule formation. Finally, future work on spatial Medicago root-AMF transcriptomics will clarify the location of these events.
Key takeaway: Understanding the symbiosis between plants and AMF is necessary for the future of agriculture. Combining single-nuclei sequencing and spatial transcriptomics will provide a more complete picture of this interaction, including individual cell types at different stages of arbuscule formation.

Plant response to "friend or foe": a cell-type-specific proteomics approach
Speaker: Maite Colinas, Max Planck Institute for Chemical Ecology, Germany The Arabidopsis root shows many cell-type-specific biotic responses. When investigating these responses, single cell transcriptomics can be challenging due to potential bias caused by protoplasting in experiments with biotic interactions. Moreover, protein-level assessments are useful because they can account for protein cell-to-cell mobility and subcellular localization. Thus, Dr. Colinas applies cell-type-specific nuclear proteomics via protein proximity labeling. This method is based on the biotinylation of interactors when a biotin ligase is fused to a protein of interest or the biotinylation of all proteins in a subcellular compartment when expressed on its own. A version called Turbo allows proximity labeling at room temperature, which has only recently become available.
In whole seedlings, Dr. Colinas has performed preliminary quantitative nuclear proteomics experiments. As a proof of concept, Dr. Colinas detected early stages of the response to the defense hormone jasmonate, demonstrating the feasibility of this approach. By expressing Turbo under the control of different cell type specific promoters, she is now preparing for cell-type-specific proximity labeling experiments. In future experiments she plans to use this method to determine whether a plant responds differently to pathogenic versus beneficial microbes. This approach may aid in answering how cell-type-specific environmental responses are regulated. Moreover, cell-type-specific proteomics data can also be combined with cell-type-specific metabolomics.
Key takeaways: Protein proximity labeling offers possibilities for identifying regulator candidates at the protein level without tissue disruption and is suitable for quantitative proteomics in response to environmental factors. In plant cells, the ER is highly motile, yet it is anchored to the plasma membrane. To probe this interaction, Dr. Brandizzi's lab performed in vivo pull-down assays and yeast two-hybrid analysis and found that the vesicle-associated protein VAP27-1 interacts with clathrin. Confocal microscopy demonstrated that clathrin is in close association with plasma membrane-ER contact sites. Moreover, endocytosis is partially disrupted in the vap27-1/3 mutant in plants, as visualized by FM4-64 internalization. This mutant also shows a delay in the formation of clathrin-coated endocytic vesicles, which could be due to a delay in the recruitment of clathrin toward the plasma membrane. Indeed, VAP27 proteins appear to recruit clathrin onto endocytic membranes. Thus, the ER contributes to the function of heterotypic membranes.
The ER network shape changes during cell development. This process requires the ER fusogen root hair defective 3 (RHD3). Loss of RHD3 can enable studies on the effects of a disrupted ER network shape. Interestingly, rhd3 mutation compromises the movement of non-ER organelles, such as the Golgi apparatus, mitochondria, and peroxisomes. For the Golgi apparatus, live imaging shows that the ER is in close association with the Golgi stacks. For endosomes, the loss of RHD3 disrupts endocytosis, indicating that the ER shape is important for the function of these organelles. Finally, the plant ER physically interacts with chloroplasts for the synthesis of important lipids. Using ER proteomics, Dr. Brandizzi's lab has identified components of this interaction in Arabidopsis. For instance, the LURE proteins define an ER subdomain in close association with chloroplasts.

Key takeaways:
The plant ER network directly contacts the actin cytoskeleton and heterotypic membranes. Efforts are unraveling the machinery responsible at the interface of the ER with other organelles. ER contacts influence the movement, positioning, and function of other organelles and membranes.

Cell-type-specific behaviors contribute to leaf growth variability in Arabidopsis
Speaker: Constance Le Gloanec, University of Montreal, Canada In developing plant organs, a morphogen gradient is present, causing a general gradient of growth in the cells; however, there is variability in the individual cell behaviors. It has been suggested that this growth variability plays a role in the acquisition of reproducible plant shapes. Therefore, Ms. Le Gloanec (PhD Candidate) is investigating the origin of growth variability.
Focusing on Arabidopsis first leaf cellular growth, Ms. Le Gloanec's work has revealed that local growth variability is highest in the leaf blade region. To determine the basis of this heterogeneity, Ms. Le Gloanec conducted investigations at the cellular level and found that stomata development appears to underlie growth variability. Indeed, the spch mutant, defective in the stomata lineage, does not show the high variability of growth observed in the wild type. Moreover, looking at the growth trajectories of different cell types aligned on the cells' differentiation time, the stomata show a distinct peak in growth during differentiation, followed by a reduction after differentiation is complete. By contrast, pavement cells show a slow reduction in growth rate over time after differentiation. Thus, the cell lineages exhibit specific behaviors. These data suggest that organ growth variability is linked to cell type precise developmental trajectories and the timing of differentiation.
Key takeaway: Cell-type-specific behaviors explain leaf growth variability, and current findings suggest that organ growth variability may result from cell-type heterogeneity in differentiation processes.

Development of targeted single-cell analysis and metabolic imaging of plants using high-spatial-resolution laser ablation electrospray ionization mass spectrometry
Speaker: Michael Taylor, Pacific Northwest National Laboratory, USA Metabolites present a functional readout of the cellular and molecular programs controlled by the expression of genes and proteins. Unlike traditional bulk omics methodologies, spatial metabolomics provides spatial information about molecular localization. In particular, laser-ablation electrospray ionization (LAESI) combined with mass spectrometry imaging enables evaluations of tissues and cells in a native state with no additives and provides the spatial distribution of molecules in an in situ fashion.
For example, with optical targeting of Allium cepa epidermal cells, LAESI can ablate individual cells to obtain a sequential metabolic profile. This approach can also be applied for single-cell analysis across cell populations to reveal metabolic profile differences. One challenge with mass spectrometry is assigning a structure to metabolites based simply on mass. These assignments require an orthogonal measurement. An ion mobility separation system combined with mass spectrometry can trap ions and separate them by size, providing two data points (i.e., size and mass) to determine structure. Finally, epifluorescence imaging can enable optically targeted ablation with LAESI. Future work will refine this technology.
Key takeaway: LAESI is a powerful spatial mass spectrometry technique for metabolomics, enabling native state analysis with little to no molecule degradation, high-throughput single-cell metabolomics, and high-resolution multimodal imaging.

Appendix S3: Community Discussion Padlet Responses
Community responses are ordered based on the number of upvotes received. These comments are intentionally unedited from the Padlet to retain the original input from the community.

Community Discussion 1
What data analysis tools and annotation standards are needed to support and centralize the community's research?
• Similar to consistent ontologies: identifying cell type marker homologues (with open expert curation to identify exceptions) across species would help transfer information between experimental systems (20 upvotes) • Developing a repository where plant and their specific cell type are listed and the data(transcriptomics, proteomics, metabolomics, tissue markers) can be deposited/accessed for the community purpose to compare with non-model organisms. • we should also establish more plant species-specific annotation (7 upvotes) • How do we know what is "standard" as tools are constantly being developed and improved? Are any of these tools being developed for plants specifically? (6 upvotes) • Data Analysis Tools: would be good to have a sandbox-type environment that enables trying out all standard and user-uploaded analysis tools as they become available Standards: Need to include all relevant metadata and annotations for published studies! (6 upvotes) • I imagine extensions of this would be needed for single-cell data, but Minimum Information about any (x) Sequence (MIxS) could be a good starting place for experimental metadata: https://gensc.org/mixs/ (5 upvotes) • A gold-standard multimodal dataset for analysis method development and benchmarking (5 upvotes) • Collated cell type-specific expression profiles (or other -omic profiles) for all published studies (5 upvotes) • For single cell (and spatial transcriptomics) data -how are cell types identified? Are these standard across publications? How can these be translated between species? (5 upvotes) • Standardization of methods and data processing, such as sequence data processing or even more difficult, standards for proteomic data, especially for quality control. • How can single cell data be integrated in gene discovery platforms such as Knetminer? (3 upvotes) • Need a central place where people can go to find these standards or tools-some things may already exist or there are related efforts (plugging AgBioData) (2 upvotes) • https://www.humancellatlas.org/data-coordination-2/ (1 upvote) • Complete (i.e. fully-sequenced) organelle genomes for all species (0 upvotes)

Community Discussion 2
What types of resources, including computational expertise and cyber-infrastructure, will the community need to best advance the science and meet its goals for broader impacts?
• sc-genomics pipelines documented as a notebook with containerized software images! (16 upvotes) • Push forward the training for data analysis, maybe a summer school for plant scdatasets (15 upvotes) • Marker gene annotation across species -Database of cell type marker genes and their corresponding orthologs/expressologs/matches across species; synteny maps of good markers; repository to record findings if marker genes translate across species. (12 upvotes) • In addition to computational resources, deposit space for sharing experimental protocols (e.g., nuclei isolation) specialized for plant species, tissue types and etc. (10 upvotes) • easy-to-use data visualizations / dashboards for casual data browsing and a repository to find them (7 upvotes) • An online space for plant sc-RNA-seq community q&a/troubleshooting. (7 upvotes) • For bioinformatics -offer hands-on workshops, especially talking about the "hows and whys" for doing certain analyses. For other techniques (isolating cells, tissue prep)repository of protocols and people to contact for additional advice for troubleshooting (7 upvotes) • Datasets and packages compatible with mainstream analysis packages/pipelines. E.g.
BSGenome packages for Signac/Seurat for model/crop species. (6 upvotes) • A centralized and extensible single-cell visualization browser so that each new study doesn't have to create its own. (6 upvotes) • we need much collaborative effort to use the potential of individual labs in dissecting cellular complexity. Its good to list the participating labs and their expertise on the PCA page for colloborations. we perform lots of single-cell work, but functional work on identified candidates is comparatively slow, that needs to be addressed. (6 upvotes) • Develop methods to integrate scRNA-seq and spatial transcriptomics to assemble different cell types into 3D/4D models. (5 upvotes) • Identify or create Gold Star datasets for teaching / new method development (4 upvotes) • Database listing specific computational expertises of members of the community so they can be contacted by other members needing assistance / input for their analyses (4 upvotes) • accessible training materials distributed freely to the community. Not everyone can attend a physical workshop so consider ways to distribute that are accessible to all. (3 upvotes) • increased social media presence for the public to get excited about plant cells (2 upvotes) • Undergraduate, High school, K-12 education outreach which integrates plant cell genomics (2 upvotes) • list of reporter lines in one place that can help in cell type/cluster annotation process for scRNA-seq data? (1 upvote) • leverage HCA: https://www.humancellatlas.org/data-coordination-2/ (0 upvotes) • Leverage https://www.humancellatlas.org/data-coordination-2/ infrastructure? (0 upvotes)

Community Discussion 3
What novel modes of organization and engagement will the community explore to catalyze new ideas, research directions, and discoveries in a time of rapid change?
• Using the PCA slack channels, we may start organizing monthly (or bi-monthly) discussion meetings with a specific topics or journal clubs to facilitate discussion and collaborations? (13 upvotes) • Brainstorming Days: Pre-defined 24 hours of asynchronous discussion focused on very specific topics/questions/ideas on a platform like Slack/Discourse etc. (11 upvotes) • Consider ideation platforms like Hype or Yambla. Establish idea caretaker community and idea processing workflow (5 upvotes) • Identify and organize groups doing/interested in the same types of data collection or analysis around common goals, encouraging collaboration (5 upvotes) • More ECR-focused events? conferences/talk series, to build more community amongst grad students/post-docs. (4 upvotes) • Database of interests and datasets being generated to allow people to more easily connect and collaborate. (3 upvotes) • DataCite has an interesting and interactive way of making their development roadmap/idea processing public. (3 upvotes) • Hype/Yambla request -Is there a link that would give some example of Hype/Yambla workflow? And how best to investigate more deeply? (2 upvotes) • The Single Cell Portal ( https://singlecell.broadinstitute.org/single_cell) might provide a template for sharing data, analysis pipelines, etc. (2 upvotes) • sub working groups like the HCA (1 upvote) • public padlet (0 upvotes) • Connect with other Atlas-type projects and model after their datastreams (0 upvotes) • public PCA workspace (0 upvotes)

Community Discussion 4
How will the community ensure that individuals and groups who are not regular participants due to disciplinary barriers, cultural differences, or resource limitations are included in the PCA?
• Much of the research is very high cost. To make it most available to the community (including people who may be excluded from data generation), having high expectations for metadata sharing, data sharing and code sharing will help to democratize. (10 upvotes) • Easy access to data sets will be important too, so efforts like EBI's scAtlas will be important (10 upvotes) • more virtual events (8 upvotes) • virtual Research Experience for Undergraduates (REU) program for single cell biology (5 upvotes) • If those individuals still part of plant community (breeders), we can have them in PCA by focusing on proposals on single cell omics on economically important traits of commercially grown varieties (such as disease tolerance, stress tolerance, apart from basic science aspect of cell biology)? (4 upvotes) • Communicating the types of questions that can be addressed with the technology -still lots of talk of "this is neat, but who cares". (4 upvotes) • promote / foster conversations and encouragements to contribute, talk about "imposter syndrome" (4 upvotes) • For the general public: increased social media presence --Maybe an Instagram plant cell photo contest? (4 upvotes) • clear code of conduct and no tolerance on harassments (4 upvotes) • invent cheaper ways of doing research (3 upvotes) • basic bioinformatics workshops for underserved high school or college students (3 upvotes) • more basic online workshops and webinars for high school and college students with no research experience (3 upvotes) • Special planning groups to understand the needs of communities of interest (3 upvotes) • training on disciplinary techniques to scientists outside of the disciplinary (3 upvotes) • create PCA chapters in underserved countries (2 upvotes) • grants to fund PCA types projects -doing all these projects are expensive, especially the sequencing! (2 upvotes) • Get undergrads to produce content for social media: tik tok, instagram, twitter (2 upvotes) • promote DIY in plant cell research (1 upvote) • promote PCA to rural america (1 upvote) • Create a panel of experts in the PCA community who could serve as mentors/advisors that people in smaller countries, rural colleges, etc. could go to for advice. (1 upvote) • Virtual events with more natural networking/discussion options (e.g. Gather.town has a easy interface for meeting people that emulates real conference experience of "walking into someone") (0 upvotes) • There are some interesting imaging DIY info out there, I don't it has been aggregated (0 upvotes) • A channel that redistribute latest development news directly from the researcher desks to all the interested audience (e.g. students, other labs) on multiple social media channels. (0 upvotes)

Community Discussion 5
In what ways will the community recruit, train, and nurture new talent to seed paradigmshifting discoveries in the future?
• Bringing onboard people from other disciplines, entertaining ideas of diverse natures, enabling them through ready to engage platforms/ collaborator teams/ events. • Expose students K-12 to gardening and emerging technologies to grow plants like vertical farming, hydroponics, shipping container farming. Make them curious first and then hit them with all these open questions they can contribute (3 upvotes) • maybe with hackaton contest (3 upvotes) • Develop educational materials for easy additions to core graduate training: conceptual, hands-on, etc (3 upvotes) • Host plant science competitions with an award at the end. E.g. seek proposals for studies in plants in space and the winner/s get their project sent by SpaceX (2 upvotes) • Really exciting presence on social media for non-scientists (or... not yet scientists) (2 upvotes) • teach plant biology at engineering schools (2 upvotes) • PCA developed fliers for exciting plant science technology needs for distributiuon to Engineering departments (2 upvotes) • Coordinate internships for graduate students at 10x genomics, Resolve, other popular commercial solutions providers (2 upvotes) • Sharing tools, creating/setting up collaborations with people not in "typical" fields of associated with PCA (e.g. evolution, ecology) (1 upvote) • Open textbooks or periodic reviews articles to outline state-of-the-art technologies (1 upvote) • Undergraduate career path materials for increased awareness of jobs in plant sciences (1 upvote) • teach how to explore the unknown as well as what's already known (1 upvote) • More training workshops to get people familiar with the single-cell datasets. Encourage people to use single-cell datasets and promote funding in the area that can attract more people to work on this area. (1 upvote) • As discussed, bringing in students and talent form outside plant science is critical. Can more be done to identify the grand challenges (and underlying motivations) to departments that attract this talent -engineering, physics, computation, chemistry etc. (0 upvotes) • For new tech development, how could the PCA help build bridges between engineering labs and departments and plant scientists? (0 upvotes) • Influence major textbook authors to get plant cell science in core undergraduate education (0 upvotes)

Community Discussion 6
How will the outcomes of the community's efforts serve the wider scientific community?
• We need to convince the wider scientific community of the value of single-cell approach to 1-better understand plant biology; 2-use of this knowledge to design new strategies to improve crop performance. (3 upvotes) • go beyond plants, inter-kingdom communities (2 upvotes) • Bringing more attention to plants as essential tools for understanding cell biology in general by building community and focus, teaming up to get the attention of animal biologists and those in industry (2 upvotes) • state / land grant universities have outreach offices (extension) that will connect you directly with farmers. can we leverage this opportunity? (2 upvotes) • Use GRC to bring the disparate communities together (2 upvotes) • education community--high school teachers (2 upvotes) • how can the single-cell community come together with the traditional plant bio community? (2 upvotes) • the results can help to understand other biological mechanisms in other organisms (2 upvotes) • sustainable, long-term place where data can be made as accessible as possible for people who are non-experts (2 upvotes) • AGBT conference would be a great venue to connect PCA with the wider community (1 upvote) • Try to influence funders to put resources into one sustainable database to house the data (1 upvote) • promote the differences between cell types and individual cells within a cell type that might not been appreciated before (1 upvote) • invite these 'outside' stakeholders, wider research community members to the GRC (0 upvotes) • how to engage industry, breeders, farmers (0 upvotes) Figure S1: How relevant and helpful was the 2021 PCA Symposium for your research? Results from survey question #1 (N=61 responses). The question was posed with a 5-point likert scale ranging from 1 (Not Helpful) to 5 (Very Helpful). 55 respondents reported a rank of 4 or 5 (~90%).    (3), community discussions (4), networking opportunities (2), talk titles in accelevents (4), time zone (2), and other (4). These comments are intentionally unedited from the survey to retain the original input from the community. This meeting was one of my 2021 highlights. I really enjoyed the talks -almost all were excellent. I also enjoyed the "working" sessions where we discussed the future of our field. I want to have more of these discussions, they were collegial and reminded me of how bright and thoughtful many of our peers are. Also, General Positive Response I think they were productive. Thanks.
I think the small poster sessions in this symposium worked better than the open structure that other virtual conferences have used, but still can't compare to a real poster session. Hopefully next year will be in person!

Constructive Criticism: Poster Sessions
arrange a flash talk slot for the poster section.

Constructive Criticism: Poster Sessions
everything was very smooth, really liked having 2-3 concurrent posters. they could be made into concurrent talks in the future rather than posters, since that might work better in a zoom setting. i think poster is good for in person experience but not for the online one.

Constructive Criticism: Poster Sessions
Most of the contributed talks were excellent. I found the level of the invited/keynote speakers way more variable (for some it was not clear to me how they fitted in the PCA theme). The Community Discussion was not very fruitful and sometimes disappointing, as a lack of expertise and well-informed opinions resulted in superficial comments, without a clear path how to turn these in concrete plans or action points. Is the goal to have follow-up meetings about points raised? Thanks for organizing this great event!

Constructive Criticism: Community Discussions
I did not find the community discussion of high level. Clearly, many people that posted questions were not well prepared (e.g. we don't need new ontologies, please explore the available (plant) ontologies or suggest modifications, if needed). A panel of experts, preparing key questions, could have delivered a more in-depth overview of outstanding questions and solutions. The presentations and poster sessions were excellent.

Constructive Criticism: Community Discussions
Can't answer questions for posters because i did not go-should have N/A option. The padlet format of the discussion was weird-I thought previous organization with breakout rooms and discussion leader was better because it seemed to encourage more participation. The padlet could be used in those and shared back to the group but I think there would have been more equitable discourse in smaller groups.

Constructive Criticism: Community Discussions
"There were a lot of community discussion sectionswhich were also great breaks! But these discussions appeared to only involve a fraction of the people -is there a way to get more people involved as well? Did we need so many of these discussions? Poster sessions were fine -I was a bit too shy to go and meet the people, but it was nice to see their posters."

Constructive Criticism: Community Discussions
The organizers made a big effort and pulled together an interesting conference. Technically everything worked well. Speakers and moderators were mostly well chosen (only in one case a moderator's comment was borderline rude). The community sessions worked well but seemed to be more useful for the organizers than for the participants. It would be good to promote more direct interactions between participants including ECRs for the next symposium. I understand it is not easy in a virtual format but there are concepts like virtual dinner tables for example. In its current format there was no chance to directly interact with others or engage in conversations.

Constructive Criticism: Networking Opportunities
More interaction with other participants would have been nice (networking/discussion "tables" or zoom rooms)

Constructive Criticism: Networking Opportunities
Next time, please be sure to include the title of the presentation immediately adjacent to each speakers name with Accelevents. It was very difficult to know what each speaker was going to cover without going back and forth between different documents.

Constructive Criticism: Talk Titles in Accelevents
It is better to have the talk titles displayed next to the names of speakers.

Constructive Criticism: Talk Titles in Accelevents
It was impossible to find talk title or topic in the agenda. I wish I could have found it in the agenda or pdf Symposium program. It is not very informative having only presenters' name and no talk title.

Constructive Criticism: Talk Titles in Accelevents
It would be great if we can see the title of the talk of each speaker in the schedule at the main stage room or the front desk.

Constructive Criticism: Talk Titles in Accelevents
The format and platform worked. Personally, the time difference didn't work for me, but still a great event! Amazing job everyone!

Constructive Criticism: Time Zone
Great symposium. The only issue I had was the early start time on the west coast so I had to miss several live talks. But of course there is no way to make it convenient for everyone, and it was great that the talks were recorded and could be watched later.

Constructive Criticism: Time Zone
Really great talks! Feedback I got from colleagues is that they were surprised a bit by the topics (scRNAand spatial transcriptiomics heavy) because in earlier adverts it sounded more metabolism focused. They said they would have submitted posters to an scRNA theme. So perhaps in the future, make it more clear ahead of time what the focus will be.

Constructive Criticism: Other
Registration was a bit confusing but was able to figure it out (had to "buy ticket" before entering the event) Constructive Criticism: Other "Everything was OK.

Constructive Criticism: Other
As a person working with 'common' gel-free proteomics and metabolomics, I am impressed with the methodological advances in plant research in recent years. I hope to establish scientific cooperation with people who perform spatial metabolomics / transcriptomics analyzes (I will start my search with people presenting the results at the PCA symposium!). So, my only remark may be: too few people not directly involved in these advanced analyses know about PCA."

Constructive Criticism: Other
Could not join community discussions General Criticism lecture should be available on youtube after session over General Criticism There were two chats, q&a and chat, it was confusing, but it was solved. General Criticism Presentawork well..discussion rounds little upset me General Criticism Table S2. What are the types of technologies you would like to hear about in a future PCA webinar? Results from survey question 5 (N=24 responses). We coded the responses into 4 categories: single cell omics (10), data analysis (4), imaging (5), and other (5). These comments are intentionally unedited from the survey to retain the original input from the community.